Estimation of genetic parameters for reproductive traits in connectedness groups of Duroc, Landrace and Yorkshire pigs in China.

The objective of this study was to estimate group- and breed-specific genetic parameters for reproductive traits in Chinese Duroc, Landrace, and Yorkshire populations. Records for reproductive traits between April 1998 and December 2017 from 92 nucleus pig breeding farms, which were involved in the China Swine Genetic Improvement Program, were analysed. Due to weak genetic connectedness across all farms, connectedness groups consisting of related farms were used. Three, two and four connectedness groups for Duroc, Landrace and Yorkshire were firstly established according to the genetic connectedness rating among farms. For each connectedness group a five-trait animal model was implemented, and via restricted maximum likelihood procedure the genetic parameters were estimated for five reproductive traits i.e., total number born (TNB), number born alive (NBA), litter weight at farrowing (LWF), farrowing interval (FI) and age at first farrowing (AFF). The average of heritabilities among connectedness groups ranged from .01 (for FI in Yorkshire) to .30 (for AFF in Duroc). Estimates of repeatability for litter traits ranged from .14 to .20 and were consistent for each breed, and for FI, the estimates varied from .01 to .11 across breeds and groups. The estimated genetic correlations among litter traits (i.e., TNB, NBA and LWF) were all significantly high (>.56) and similar across breeds. Averaged genetic correlations over three breeds were -.25, -.27, -.18, -.04, -.10, -.02, and .28 for FI-TNB, FI-NBA, FI-LWF, AFF-TNB, AFF-NBA, AFF-LWF and FI-AFF, respectively. The standard errors of the estimates were all very low (<0.01) in most situations. Results from this study suggest that selection based on TNB which is currently used in dam line selection index can improve NBA and LWF simultaneously. However, care should be taken on FI and AFF as they are both greatly influenced by non-genetic factors such as management and measurement.

Selection signature reveals genes associated with susceptibility loci affecting respiratory disease due to pleiotropic and hitchhiking effect in Chinese indigenous pigs.

BACKGROUND: Porcine respiratory disease is one of the most important health problems which causes significant economic losses. OBJECTIVE: To understand the genetic basis for susceptibility to swine enzootic pneumonia (EP) in pigs, we detected 102,809 SNPs in a total of 249 individuals based on genome-wide sequencing data. METHODS: Genome comparison of three susceptibility to swine EP pig breeds (Jinhua, Erhualian and Meishan) with two western lines that are considered more resistant (Duroc and Landrace) using XP-EHH and FST statistical approaches identified 691 positively selected genes. Based on QTLs, GO terms and literature search, we selected 14 candidate genes that have convincible biological functions associated with swine EP or human asthma. RESULTS: Most of these genes were tested by several methods including transcription analysis and candidated genes association study. Among these genes: CYP1A1 and CTNNB1 are involved in fertility; TGFBR3 plays a role in meat quality traits; WNT2, CTNNB1 and TCF7 take part in adipogenesis and fat deposition simultaneously; PLAUR (completely linked to AXL, r2=1) plays an essential role in the successful ovulation of matured oocytes in pigs; CLPSL2 (strongly linked to SPDEF, r2=0.848) is involved in male fertility. CONCLUSION: These adverse genes susceptible to swine EP may be selected while selecting for economic traits (especially reproduction traits) due to pleiotropic and hitchhiking effect of linked genes. Our study provided a completely new point of view to understand the genetic basis for susceptibility or resistance to swine EP in pigs thereby, provide insight for designing sustainable breed selection programs. Finally, the candidate genes are crucial due to their potential roles in respiratory diseases in a large number of species, including human.

Application of partial least squares in exploring the genome selection signatures between populations.

Natural and artificial selection have led to substantial variation in the phenotypic traits of different populations. Therefore, there is a need to develop methods that are based on cross-population comparisons to discover loci related to specific traits. Here, we suggested a strategy to detect the genome selection signatures between populations based on the partial least squares (PLS) theory. Using the binary population indicator as the response variable in the PLS analysis, alleles under selection between populations were identified from the first PLS component. We explored the theory behind the PLS analysis to reveal its usefulness in detecting the loci under selection. Through the simulation study, the results showed that the PLS method had a better performance than the FST and EigenGWAS methods. In addition, by using the real data hapmap3, we found that rs11150606 in PRSS53 gene and rs1800414 in OCA2 gene were under selection between East Asian populations and three other populations, including African, American, and European populations. We concluded that this strategy was easily carried out and might supplement for the deficiency of the EigenGWAS method in some cases. To facilitate the application of this method, we developed an R script that is freely accessible at http://klab.sjtu.edu.cn/PLS/ .

Assessment of Autozygosity Derived From Runs of Homozygosity in Jinhua Pigs Disclosed by Sequencing Data.

Jinhua pig, a well-known Chinese indigenous breed, has evolved as a pig breed with excellent meat quality, greater disease resistance, and higher prolificacy. The reduction in the number of Jinhua pigs over the past years has raised concerns about inbreeding. Runs of homozygosity (ROH) along the genome have been applied to quantify individual autozygosity to improve the understanding of inbreeding depression and identify genes associated with traits of interest. Here, we investigated the occurrence and distribution of ROH using next-generation sequencing data to characterize autozygosity in 202 Jinhua pigs, as well as to identify the genomic regions with high ROH frequencies within individuals. The average inbreeding coefficient, based on ROH longer than 1 Mb, was 0.168 ± 0.052. In total, 18,690 ROH were identified in all individuals, among which shorter segments (1-5 Mb) predominated. Individual ROH autosome coverage ranged from 5.32 to 29.14% in the Jinhua population. On average, approximately 16.8% of the whole genome was covered by ROH segments, with the lowest coverage on SSC11 and the highest coverage on SSC17. A total of 824 SNPs (about 0.5%) and 11 ROH island regions were identified (occurring in over 45% of the samples). Genes associated with reproduction (HOXA3, HOXA7, HOXA10, and HOXA11), meat quality (MYOD1, LPIN3, and CTNNBL1), appetite (NUCB2) and disease resistance traits (MUC4, MUC13, MUC20, LMLN, ITGB5, HEG1, SLC12A8, and MYLK) were identified in ROH islands. Moreover, several quantitative trait loci for ham weight and ham fat thickness were detected. Genes in ROH islands suggested, at least partially, a selection for economic traits and environmental adaptation, and should be subject of future investigation. These findings contribute to the understanding of the effects of environmental and artificial selection in shaping the distribution of functional variants in the pig genome.

Exploring the Structure of Haplotype Blocks and Genetic Diversity in Chinese Indigenous Pig Populations for Conservation Purpose.

Chinese indigenous pigs in the Taihu Lake region are well known for their high fecundity and other excellent characteristics. To better understand the characteristics of these breeds in this area as well as to provide the government and breeders the molecular basis for formulating a reasonable conservation policy, we explored the structure of haplotype blocks and genetic diversity of the 7 populations which is relevant for the management and conservation of these important genetic resources using next-generation sequencing data. In this study, a total of 131 300 single-nucleotide polymorphisms with minor allele frequencies ⩾0.05 were obtained for further analysis. In general, there are similar within-breed genetic diversities (He, Ho, Pn, Ar) among these 7 pig populations in the Taihu Lake region. Average values for the inbreeding coefficients estimates in the 7 populations are 0.110 (F1), 0.056 (F2), and 0.078 (F3). All the breeds have seen a continuous decline in Ne estimates over time with FJ and SW populations having a very similar curve. Moreover, the Ne of SMS pig breeds were smaller than other Chinese pig breeds, indicating that SMS pig breeds underwent stronger selection pressure than other Chinese pig breeds. The average genetic distances among the 7 populations in the Taihu Lake region were 0.235 (MMS), 0.240 (SMS), 0.269 (EH), 0.248 (MI), 0.221 (FJ), 0.254 (JX), and 0.212 (SW). A summary of the number of haplotype blocks and haplotype diversity was also presented. This study provide a deep understanding of the current situation of conservation in this region, thereby uncovering the pertinent insight to better formulate more reasonable preservation policies for the government departments and breeding planners to follow-up.

Genome-Wide and Trait-Specific Markers: A Perspective in Designing Conservation Programs.

Nowadays, breed conservation has entered the genomics era and it is imperative to develop novel theory to design the breeding schemes of the conservation populations by using the genomic information. The genome-wide markers have been regarded as a useful strategy to maintain genetic diversity. However, using the genome-wide SNPs to optimize diversity might not be optimal for some specific loci associated with specific-traits. Using the sequencing data of the conserved population of the Saba pig breed, we demonstrated that the conservation program designed by using the genome-wide SNPs might result in the loss of the genetic diversity of the reproduction trait. We suggested an idea of using phylogenetic tree to select valuable individuals for conservation program based on the genome-wide and trait-specific makers. The selection rule was to make the selected samples to be widely distributed as much as possible in both the genome-wide and trait-specific phylogenetic trees.

The genetic connectedness calculated from genomic information and its effect on the accuracy of genomic prediction.

The magnitude of connectedness among management units (e.g., flocks and herds) gives a reliable estimate of genetic evaluation across these units. Traditionally, pedigree-based methods have been used to evaluate the genetic connectedness in China. However, these methods have not been able to yield a substantial outcome due to the lack of accuracy and integrity of pedigree data. Therefore, it is necessary to ascertain genetic connectedness using genomic information (i.e., genome-based genetic connectedness). Moreover, the effects of various levels of genome-based genetic connectedness on the accuracy of genomic prediction still remain poorly understood. A simulation study was performed to evaluate the genome-based genetic connectedness across herds by applying prediction error variance of difference (PEVD), coefficient of determination (CD) and prediction error correlation (r). Genomic estimated breeding values (GEBV) were predicted using a GBLUP model from a single and joint reference population. Overall, a continued increase in CD and r with a corresponding decrease in PEVD was observed as the number of common sires varies from 0 to 19 regardless of heritability levels, indicating increasing genetic connectedness between herds. Higher heritability tends to obtain stronger genetic connectedness. Compared to pedigree information, genomic relatedness inferred from genomic information increased the estimates of genetic connectedness across herds. Genomic prediction using the joint versus single reference population increased the accuracy of genomic prediction by 25% and lower heritability benefited more. Moreover, the largest benefits were observed as the number of common sires equals 0, and the gain of accuracy decreased as the number of common sires increased. We confirmed that genome-based genetic connectedness enhanced the estimates of genetic connectedness across management units. Additionally, using the combined reference population substantially increased accuracy of genomic prediction. However, care should be taken when combining reference data for closely related populations, which may give less reliable prediction results.

Exploring the Genetic Correlation Between Growth and Immunity Based on Summary Statistics of Genome-Wide Association Studies.

The relationship between growth and immune phenotypes has been presented in the context of physiology and energy allocation theory, but has rarely been explained genetically in humans. As more summary statistics of genome-wide association studies (GWAS) become available, it is increasingly possible to explore the genetic relationship between traits at the level of genome-wide summary statistics. In this study, publicly available summary statistics of growth and immune related traits were used to evaluate the genetic correlation coefficients between immune and growth traits, as well as the cause and effect relationship between them. In addition, pleiotropic variants and KEGG pathways were identified. As a result, we found negative correlations between birthweight and immune cell count phenotypes, a positive correlation between childhood head circumference and eosinophil counts (EO), and positive or negative correlations between childhood body mass index and immune phenotypes. Statistically significant negative effects of immune cell count phenotypes on human height, and a slight but significant negative influence of human height on allergic disease were also observed. A total of 98 genomic regions were identified as containing variants potentially related to both immunity and growth. Some variants, such as rs3184504 located in SH2B3, rs13107325 in SLC39A8, and rs1260326 located in GCKR, which have been identified to be pleiotropic SNPs among other traits, were found to also be related to growth and immune traits in this study. Meanwhile, the most frequent overlapping KEGG pathways between growth and immune phenotypes were autoimmune related pathways. Pleiotropic pathways such as the adipocytokine signaling pathway and JAK-STAT signaling pathway were also identified to be significant. The results of this study indicate the complex genetic relationship between growth and immune phenotypes, and reveal the genetic background of their correlation in the context of pleiotropy.